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Energy consumption optimization for green Device-to-Device multimedia communications

机译:绿色设备间多媒体通信的能耗优化

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Recently, Device-to-Device (D2D) multimedia communications have been envisioned as emerging technology for improving capacity and reducing power consumption in wireless networks. In D2D multimedia communications, multimedia applications consume considerable amount of energy and bandwidth resources to satisfy increasing mobile user demands. To overcome this problem, we have proposed a novel energy consumption optimization method (ECO) for green D2D multimedia communications by using Adaptive Genetic Algorithm. In particular, we first encode the videos by using layered multiple description coding with forward error correction (LMDC-FEC) to protect against error and delays as well as more adaptive to unstable bandwidth in wireless channels. To minimize the average energy consumption by packetizing and transmitting, we then formulate the energy consumption optimization problem and solve it to find out the optimal encoding rate matrix allocated to each video under limited bandwidth resource and high quality constraints. The experimental results demonstrated that our proposed ECO method can achieve remarkable improvements in terms of energy saving, i.e., save up to 64% average energy consumption compared to the other methods, while ensuring high received video quality and satisfying given limited bandwidth.
机译:最近,设备到设备(D2D)多媒体通信已被视为新兴技术,用于提高无线网络的容量并降低功耗。在D2D多媒体通信中,多媒体应用会消耗大量的能量和带宽资源,以满足不断增长的移动用户需求。为了克服这个问题,我们提出了一种采用自适应遗传算法的绿色D2D多媒体通信能耗优化方法(ECO)。特别是,我们首先通过使用带有前向纠错(LMDC-FEC)的分层多描述编码来对视频进行编码,以防止错误和延迟,以及更适应无线信道中的不稳定带宽。为了通过打包和传输将平均能耗降至最低,我们制定了能耗优化问题,并对其进行求解,以找出在带宽资源有限和质量受限的情况下分配给每个视频的最佳编码率矩阵。实验结果表明,我们提出的ECO方法可以在节能方面取得显着改善,即与其他方法相比,可以节省多达64%的平均能耗,同时确保高接收视频质量并满足给定的有限带宽。

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